1. Field of the Invention
The present invention relates in general to the field of analog-to-digital conversion circuits or converters (ADCs).
2. Description of the Related Art
Analog-to-digital converters (ADCs) are commonly used in several applications (for example, in the telecommunication field), whenever an analog input signal is to be converted into a corresponding digital output signal. The basic component of every converter is a quantizer. The quantizer compares an analog signal with one or more predefined threshold values; the combination of the results of the comparisons uniquely identifies the digital representation of the analog signal. In order to achieve a high resolution of the whole converter, quantizer of the parallel type are commonly used; in this case, the analog signal is compared with multiple threshold values at the same time.
However, the inherent imprecision of the technological processes used to implement the converter brings about an error in each threshold value of the quantizer. The error has a common component (equal to the mean value of the errors in all the threshold values) and a differential component (equal to the error in each threshold value minus the common component). The differential error causes a harmonic distortion in the resulting digital signal, which distortion jeopardizes the linearity of the whole converter; instead, the common component introduces an offset in the digital signal.
Many solutions are known in the art for reducing the effects of the differential errors in the digital signal. Conversely, the offset errors have been (wrongly) deemed not particularly deleterious for the performance of the converter; therefore, the effects of the offset errors have not been investigated thoroughly.
Particularly, some converters (such as the converters of the sigma-delta type) implement a feedback loop that compensates the offset errors to a certain extent (without adversely affecting the accuracy of the converter). However, different remarks apply to converters having a multistage architecture. In this case, the converter includes a sequence of cascade-connected stages providing successive approximations of the digital output signal. For this purpose, each stage performs a low-resolution conversion; a residue of the corresponding analog signal, representing a quantization error of the conversion, is then amplified by an inter-stage gain and passed to a next stage in the sequence (so as to ensure that each stage operates with a similar input signal range).
As a consequence, the offset error in the quantizer of each stage (with the exception of the last one) affects the dynamic range of the analog signal that is input to the next stages; this change in the dynamic range can cause an overflow in the respective quantizer. The problem is particular acute in the first stages of the converter (since the corresponding offset error is amplified by all the next stages).
The only solution known in the art for solving the above-mentioned problem is to scale down the analog signal that is input to the next stages of the converter; this result is achieved reducing the corresponding inter-stage gain, and then the dynamic range of the analog signal. However, the proposed solution strongly reduces the actual resolution that can be achieved by the converter.
This drawback is particular acute in applications working with wide-band signals and requiring high resolutions (for example, in modern mobile telecommunication techniques such as the UMTS). In this case, a commonplace solution is that of using a sigma-delta (ΣΔ), or delta-sigma (ΔΣ) architecture.
In a sigma-delta converter, the analog input signal is oversampled at a rate far higher than the one of the Nyquist theorem (i.e., twice the bandwidth of the signal); the oversampling spreads the quantization error power over a large band, so that its density in the band of the analog input signal is reduced; typical values of an OverSampling Rate (OSR) are from 32 to 64. The sigma-delta converter reacts to the changes in the analog input signal, thereby performing a delta modulation (from which the name “delta”). A corresponding analog delta signal is applied to one or more filters (through a feed-back loop). Each filter integrates the analog delta signal (from which the name “sigma”), and contours the quantization error so that its spectrum is not uniform; this process (known as noise shaping) pushes the quantization error power out of the band of the analog input signal. The resulting analog signal is quantized by means of a very low resolution ADC (typically, at 1 bit). The digital signal so generated is filtered, in order to suppress the out-of-band quantization error; at the same time, a decimator downsamples the digital signal extracting higher resolution at a lower rate. This architecture provides good performance at very low cost.
The number of filters, in the sigma-delta converter defines the degree of noise-shaping (referred to as the order of the sigma-delta converter). Sigma-delta converters with a single-loop structure are typically designed with an order of one or two because of instability problems. Whenever a higher order is required, a multistage architecture implementing two or more loops is commonly used. A multistage architecture including at least one sigma-delta converter, also known as MASH (MultistAge noise SHaping), is inherently stable; moreover, a MASH converter provides performance comparable to the one of a single-loop converter having an order equal to the sum of the orders of the different stages of the MASH converter.
Additional problems arise with wide-band signals. In this case, the sampling frequency of the analog input signal is limited by the technological restraints, so that the oversampling rate must be relatively low (for example, 4–8). Moreover, the use of sigma-delta converters of high order is substantially useless, since the noise-shaping is unable to push the quantization error out of the (wide) band of interest. Therefore, the resolution of the quantizer included in every stage of the sigma-delta converter is the last parameter on which it is possible to act, in order to achieve the desired performance (thereby introducing the offset errors described above).
Accordingly, there exists a need for overcoming the disadvantages of the prior art as discussed above.